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Record W3131800725 · doi:10.1016/j.vaccine.2021.01.070

Similar impact and replacement disease after pneumococcal conjugate vaccine introduction in hospitalised children with invasive pneumococcal disease in Europe and North America

2021· article· en· W3131800725 on OpenAlexaffabout
Arto A. Palmu, Philippe De Wals, Maija Toropainen, Shamez Ladhani, Geneviève Deceuninck, Mirjam J. Knol, Elisabeth A. M. Sanders, Elizabeth Miller

Bibliographic record

VenueVaccine · 2021
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsCentre hospitalier universitaire de QuébecUniversité Laval
FundersSanofiGlaxoSmithKlinePfizer
KeywordsPneumococcal conjugate vaccineMedicinePneumococcal diseaseIncidence (geometry)PediatricsStreptococcus pneumoniaePneumococcal infectionsSerotypeVaccinationAntibioticsVirology

Abstract

fetched live from OpenAlex

High incidence of childhood invasive pneumococcal disease (IPD) in the US declined steeply after 7-valent pneumococcal conjugate vaccine (PCV7) introduction, outweighing reductions observed elsewhere. We re-analysed aggregate published data and compared pre- and post-PCV IPD-incidence in different countries to explore PCV impact on hospitalised and outpatient IPD separately. The proportion of hospitalised IPD cases was consistently high (>80%) in England&Wales, Finland, the Netherlands, and Quebec/Canada, but only 32% in the US before PCV introduction, increasing to 69% during the PCV era. In the US, a higher reduction in outpatient IPD incidence (94% in 2015 versus 1998-99) was observed compared to hospitalised IPD (79%); a 51% reduction in the non-PCV13-type IPD incidence among outpatient cases was estimated compared to a >2-fold increase for hospitalised cases. After stratification by hospitalization status, PCV programmes resulted in similar impact and serotype replacement in hospitalised IPD in US when compared to other countries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.227
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2021
Admission routes2
Has abstractyes

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